import gradio as gr
from PIL import Image
from datetime import datetime
import pytz
from ocr_engine import extract_weight
from simple_salesforce import Salesforce
import base64
import os

# Salesforce credentials (for safety, you can later store these in environment variables)
SF_USERNAME = "Autoweightlogger@sathkrutha.com"
SF_PASSWORD = "autoweight@32"
SF_TOKEN = "UgiHKWT0aoZRX9gvTYDjAiRY"

# Connect to Salesforce
sf = Salesforce(username=SF_USERNAME, password=SF_PASSWORD, security_token=SF_TOKEN)

def process_image(image):
    if image is None:
        return "❌ No image provided", "", None, gr.update(visible=True)
    try:
        weight = extract_weight(image)
        ist = pytz.timezone('Asia/Kolkata')
        timestamp = datetime.now(ist).strftime("%Y-%m-%d %H:%M:%S IST")
        if not weight or "No valid" in weight:
            return "❌ Unable to detect. Try again with a clearer image.", "", image, gr.update(visible=True)

        # Save snapshot image to base64 (optional field, depends on usage)
        buffered_image = image.copy()
        buffered_image.save("snapshot.jpg")
        with open("snapshot.jpg", "rb") as img_file:
            snapshot_base64 = base64.b64encode(img_file.read()).decode('utf-8')

        # Create record in Salesforce
        sf.Weight_Log__c.create({
            "Captured_Weight__c": float(weight.replace("kg", "").strip()),
            "Captured_At__c": datetime.now(ist).isoformat(),
            "Snapshot_Image__c": snapshot_base64,
            "Device_ID__c": "DEVICE-001",   # Static or dynamic based on your design
            "Status__c": "Captured"
        })

        return weight, timestamp, image, gr.update(visible=False)
    except Exception as e:
        return f"Error: {str(e)}", "", None, gr.update(visible=True)

with gr.Blocks(css=".gr-button {background-color: #2e7d32 !important; color: white !important;}") as demo:
    gr.Markdown("""
    <h1 style='text-align: center; color: #2e7d32;'>📷 Auto Weight Logger</h1>
    <p style='text-align: center;'>Upload or capture a digital weight image. Detects weight using AI OCR.</p>
    <hr style='border: 1px solid #ddd;'/>
    """)

    with gr.Row():
        image_input = gr.Image(type="pil", label="📁 Upload or Capture Image")

    detect_btn = gr.Button("🚀 Detect Weight")

    with gr.Row():
        weight_out = gr.Textbox(label="📦 Detected Weight", placeholder="e.g., 97.9 kg", show_copy_button=True)
        time_out = gr.Textbox(label="🕒 Captured At (IST)", placeholder="e.g., 2025-07-01 12:00:00")

    snapshot = gr.Image(label="📸 Snapshot Preview")
    retake_btn = gr.Button("🔁 Retake / Try Again", visible=False)

    detect_btn.click(fn=process_image, inputs=image_input, outputs=[weight_out, time_out, snapshot, retake_btn])
    retake_btn.click(fn=lambda: ("", "", None, gr.update(visible=False)),
                     inputs=[], outputs=[weight_out, time_out, snapshot, retake_btn])

demo.launch()